This patent is focused on the methods for retaining telephony clients by means of recommending plans which reduce the cost for the customer. The concept of recommendation has been present in literature for a long time and has given rise to a variety of patents such as “Method and Apparatus for Item Recommendation using Automated Collaborative Filtering” of Microsoft Corporation [1], “System and Methods for Collaborative Recommendations” of Amazon Inc. [2], as well as others from smaller companies such as Neonics Inc. [3] or Athenium LLC [4] [5]. All these patents generally have similar recommendation algorithms based on collaborative filtering, which recommend items to users based on similar preferences. In the literature there are also other patents which have problems similar to the one detailed herein, for example bank credit recommendation [6], which is solved using a decision tree, and insurance recommendation [8], solved by means of a series of interactions with the user.
Although the concepts set forth in the state of the art are similar to the method proposed herein, the type of problem and the way to solve it make the method proposed in this patent completely different.
In the telecommunications field there are patents with similar functionality to the proposed method, such as “Method of Selecting the Most Cost Effective Cellular Service Plan provided by Cellular Telephone Resellers to Multi-Line Customers” [8] of Motorola, which is focused on the problem of the recommendation of plans but only for users who have more than one line contracted or “System and Method for Recommending a Wireless product to a User” [9] which recommends a plan to a user based on the answers they give in a survey. More related to the proposed method are the patents “Method of Selecting a cost effective Service Plan” [10] of Motorola and “System and Method for Determining Optimal Wireless Communication Service Plans” [11] of Traq Wireless. Both patents propose a solution to the same problem which is tackled with the method proposed in this patent.
The present invention focuses on a different problem aimed at the method used in call centers of mobile operators, as shown in FIG. 1. The intention is to provide a different approach to the conception of the call centers, adding to the standards established in said systems (boxes 1 to n), at least one additional box and the flow marked in a dashed line corresponds to the new recommendation system proposed in the present invention, in which the process which will be detailed below is included.
The state of art of recommending mobile telephony plans for customers is focused on achieving the best offer for the customer [10] [11] [12], but it forgets many factors in a competitive environment (number of operators existing on the market, importance thereof, customer value, the operator which the user calls most frequently, difference between the billing with the current offer and the competition, better offers available on the market and better offers by the operator). In the case of reference [10], the main limitations are: (1) the system is based on processing call detail records or CDRs, and generally an operator cannot be expected to store the CDRs of all its users for an indefinite time period, this implies that the recommendation can only be made considering the last months of traffic and therefore seasonality problems can be incurred and (2) the recommendation of the plan is made by only considering which plan saves more money for the customer, without considering the position of the operator. Likewise, the method set forth in [11] and [12] only provides the recommendation of a plan in which the user saves more money. The invention set forth herein differs from the previous ones in that (1) the bill of the plans is not calculated by using CDRs but rather an aggregated representation of the behavior of each user, whereby the need to store the CDRs is prevented and it allows preventing the seasonality problem of the data; (2) the recommendation of the plan is made by not only considering the saving of the customer but also other factors including: (a) the level of risk of the customer going to the competition; (b) the ARPU (Average Revenue per User) of the customer in question and (c) the strategy of the company. Thus, the intention is to retain the customer by recommending a plan which involves a saving for him but also considering within those possibilities, the one which most favors the operator.